Explore-LC- Uniting Existing Real-World DATA Sources to Create a NOVEL ASIA-Pacific Wide Research Platform for NON-SMALL CELL LUNG Cancer

Author(s)

Horsburgh D1, Song S1, Kim J2, Ng JYS1, Kim JA2, Patel D1
1IQVIA Asia Pacific, Singapore, Singapore, 2IQVIA, Seoul, Korea, Republic of (South)

OBJECTIVES: Despite the increasing incidence of non-small cell lung cancer (NSCLC) in Asia-Pacific, real-world evidence on patient characteristics, treatment, and outcomes is siloed into clinical trial results and national registries. There is currently no way to track the rapidly changing landscape of lung cancer management across APAC. The EXPLORE-LC program will build a network of treating clinicians and high-quality real-world data sources (RWDS) to carry out real-world research.

METHODS: EXPLORE-LC will be a coordinated meta-analysis of lung cancer databases across APAC. At its core will be a retrospective cohort design with the primary objective of understanding real-world outcomes of all stage NSCLC patients and by stage at diagnosis. It will also describe clinical characteristics and treatment patterns from diagnosis until lost to follow-up or death.

Using common data specifications, specific lung cancer variables will be extracted from source data into a locally-maintained EXPLORE-LC data fie, including derived variables such as line of therapy. Standardized analyses will be run off the common EXPLORE-LC data file to generate source-specific summary statistics, with these then pooled together through national and regional-level meta-analyses. Variables analyzed will include histological sub-type, biomarker status, initial treatment, line of therapy and treatment sequencing, as well overall survival, treatment duration and time to next treatment.

RESULTS: EXPLORE-LC will be launched through a pilot study at two large hospitals in South Korea, to begin in Q1 2020 and to analyze over 4,000 NSCLC cases.

CONCLUSION: EXPLORE-LC will generate insights into the NSCLC population, management and outcomes that have historically been visible only at a national level. The use of aggregate statistics ensures data privacy and reduces regulatory hurdles which have limited similar efforts in the past and allows for scaling to include additional RWDS, including administrative and genomics data to further explore sub-populations with Asia-Pacific and uncover unmet needs.

Code

PCN12

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